Privacy-Aware Infrastructure in the AI-Native Era: An Asset Classification Case Study

This post details Meta's hybrid pattern for privacy-aware infrastructure (PAI) asset classification at scale, focusing on the 'Understand' layer. It introduces a system that builds rich context before using LLMs to handle ambiguity and novelty, distilling stable behavior into deterministic, versioned rules for routine enforcement. The system prioritizes context over prompts, decouples evaluation from optimization, and uses a two-lane operating pattern (deterministic and LLM fallback) with offline adjudication and rule promotion. The core contribution is a practical, staged approach to classifying data assets for privacy controls, balancing reasoning under ambiguity with the need for explainable and reproducible enforcement.